The challenge in quantitative human risk assessment of carcinogenic exposure lies in the need to account for inter-individual variation in susceptibility that may occur in any phase of carcinogenesis. The goal of this project is to construct multiple risk models for identifying susceptibility markers for lung cancer. This proposal is build upon existing resources (molecular and epidemiological data). In these studies, a panel of markers of susceptibility (including in vitro bleomycin-induced chromatid breaks), DNA repair capacity, several metabolic polymorphisms) is being applied to newly diagnosed lung cancer cases and controls matched by age, gender, ethnicity and smoking status. Few previous case-control studies of lung cancer have had the sample size, ethnic diversity, and range of markers that we have available for risk assessment. We list the following specific aims: 1. To build a risk assessment model to incorporate available susceptibility markers simultaneously in the model, in order to determine the association between a particular marker and risk of lung cancer when adjusted by other markers and other covariates of interest such as smoking status. 2. To determine interaction effects between markers of susceptibility. We expect to determine whether there is an interaction effect between the markers, when they are adjusted by groups of life style and demographic variables. We propose a multi-variate model that incorporates mixed and continuous variables as outcome response. Refinement of the risk assessment process has implications for primary and secondary prevention interventions.